R Notebook

Fun example for learning dplyr and tidyr not to be used for interpretation or analysis. Customized from here: https://rpubs.com/cholland9/885458

County population downloaded from here https://www.census.gov/data/tables/time-series/demo/popest/2020s-counties-total.html#par_textimage

Example data is for Cali and Indiana

co-est2021-pop-06.xlsx - cali co-est2021-pop-18 (1) - Indy

library(tidyverse)

Warning: package ‘tidyverse’ was built under R version 4.0.4Registered S3 methods overwritten by 'dbplyr':
  method         from
  print.tbl_lazy     
  print.tbl_sql      
── Attaching packages ──────────────────────────────────────── tidyverse 1.3.1 ──
✔ ggplot2 3.3.5      ✔ purrr   0.3.4 
✔ tibble  3.1.4      ✔ dplyr   1.0.10
✔ tidyr   1.2.1      ✔ stringr 1.5.0 
✔ readr   2.0.1      ✔ forcats 0.5.1 
Warning: package ‘ggplot2’ was built under R version 4.0.5Warning: package ‘tibble’ was built under R version 4.0.5Warning: package ‘tidyr’ was built under R version 4.0.5Warning: package ‘readr’ was built under R version 4.0.5Warning: package ‘purrr’ was built under R version 4.0.3Warning: package ‘dplyr’ was built under R version 4.0.5Warning: package ‘stringr’ was built under R version 4.0.5Warning: package ‘forcats’ was built under R version 4.0.3── Conflicts ─────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()

covid_raw <- read_csv("https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_US.csv")

Rows: 3342 Columns: 1097── Column specification ───────────────────────────────────────────────────────────────────
Delimiter: ","
chr    (6): iso2, iso3, Admin2, Province_State, Country_Region, Combined_Key
dbl (1091): UID, code3, FIPS, Lat, Long_, 1/22/20, 1/23/20, 1/24/20, 1/25/20, 1/26/20, ...
ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

nrow (covid_raw)

[1] 3342

ncol(covid_raw)

[1] 1097

covid <- select(covid_raw, state= "Province_State", county= "Admin2", contains("/") )

covid

nrow(covid)

[1] 3342

ncol(covid)

[1] 1088

covid <- filter(covid, state== "California")

nrow(covid)

[1] 60

ncol(covid)

[1] 1088

covid_long <- pivot_longer(covid, names_to = "date", values_to = "c_cases", cols = contains("/"))

covid_long

nrow(covid_long)

[1] 65160

library(lubridate)

Warning: package ‘lubridate’ was built under R version 4.0.5Loading required package: timechange
Warning: package ‘timechange’ was built under R version 4.0.5
Attaching package: ‘lubridate’

The following objects are masked from ‘package:base’:

    date, intersect, setdiff, union

covid_long <- mutate(covid_long, date=mdy(date))
covid_long

covid_long <- filter(covid_long, date <= as.Date("2022-02-15"))

nrow(covid_long)

[1] 45360

covid_long <- group_by(covid_long, county)

covid_long <- arrange(covid_long, date)

covid_long <- mutate(covid_long, cases = c_cases - lag(c_cases, n=1L, default=0))

covid_last <- summarize (covid_long, total_cases=sum(c_cases))
nrow(covid_last)

[1] 60

ncol(covid_last)

[1] 2

covid_last

library(readxl)
mnpops <- read_excel("co-est2021-pop-06.xlsx")
mnpops

NA

covid_last <- inner_join(covid_last, mnpops)

Joining, by = "county"

covid_last

covid_last <- mutate(covid_last, per100k = total_cases / pop2020 * 100000)

covid_last

top10 <- slice_max(covid_last, per100k, n=10)
top10